The goal of this SBIR project is to design a cost-effective, lightweight, integrated, whole-head dense-array electroencephalography and near-infrared spectroscopy (dEEG/NIRS) brain imaging and data analysis system for non-invasive recording of brain activity in neonates and young children. This system will permit bedside monitoring of immediate at-risk neonates, and early identification and intervention for abnormalities that predict developmental disabilities and cognitive deficits. A dense array of 128 combined optoelectrodes sitting on the surface of the scalp will simultaneously record brain electrical activity (EEG), and cerebral blood oxygenation changes (NIRS), providing complementary measures of brain function. Having demonstrated feasibility in Phase I with a partial array and single modulated wavelength, the first Specific Aim in Phase II is to extend the approach to complete a commercially viable, whole-head and dual-wavelength dEEG/NIRS acquisition system for infants. The existing design will be modified to use dual-wavelength LED emitters for hemoglobin measurements, with enhanced stability and robustness of the integrated optoelectrodes. New architecture will modulate up to 64 NIR light sources (32 dual-wavelength LEDs) at different frequencies and demodulate signals from up to 96 detectors. NIRS data acquisition software will be refined and further improvements will be made to the integration and synchronization with other acquisition streams, including Net Station EEG, Polygraphic Input Box data (e.g., ECG, EMG), and E-Prime experimental control software. The second Specific Aim is to design commercial, advanced data analysis tools for accurate computation of blood oxygenation changes measured with integrated dEEG/NIRS sensors. This NIRS analysis software will complement EGI's existing EEG processing and source analysis software. The first step will be to implement standard computational tools (based on the modified Beer-Lambert equation) that are used to determine changes in oxy- and deoxy-hemoglobin as measured by recovered NIR signals. Then, the computational parameters will be refined through advanced anatomical infant head modeling, and numerical modeling of the path, scattering, and absorption properties of NIR light through infant head tissues. The third Specific Aim will test and validate the integrated dEEG/NIRS system hardware and software for data integrity, functionality, and usability. Simultaneous dEEG and NIR data will be collected with the complete 128-sensor system during resting state and functional tasks in 30 neonates. The functional data task wil present simple speech and matched non-speech sounds that have previously resulted in individual differences in brain electrical patterns predictive of later dyslxia diagnosis. Outputs from in-house NIRS analysis tools will be cross validated with existing open-source analysis tools (e.g., HomER). Usability of the acquisition and analysis software will be assessed and further refinements made. Finally, commercial user guides for hardware, acquisition software, and analysis software will be prepared to accompany the dEEG/NIRS acquisition and analysis product.